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Computational-based approach for predicting porosity of electrospun nanofiber mats using response surface methodology and artificial neural network methods
, Article Journal of Macromolecular Science, Part B: Physics ; Volume 54, Issue 11 , 2015 , Pages 1404-1425 ; 00222348 (ISSN) ; Khodaparast Haghi, A ; Kasaei, S ; Hasanzadeh, M ; Sharif University of Technology
Taylor and Francis Inc
2015
Abstract
Comparative studies between response surface methodology (RSM) and artificial neural network (ANN) methods to find the effects of electrospinning parameters on the porosity of nanofiber mats is described. The four important electrospinning parameters studied included solution concentration (wt.%), applied voltage (kV), spinning distance (cm) and volume flow rate (mL/h). It was found that the applied voltage and solution concentration are the two critical parameters affecting the porosity of the nanofiber mats. The two approaches were compared for their modeling and optimization capabilities with the modeling capability of RSM showing superiority over ANN, having comparatively lower values of...